Two- and Three-Dimensional Benchmarks for Particle Detection from an Industrial Rotary Kiln Combustion Chamber Based on Light-Field-Camera Recording
This paper describes a benchmark dataset for the detection of fuel particles in 2D and 3D image data in a rotary kiln combustion chamber. The specific challenges of detecting the small particles under demanding environmental conditions allows for the performance of existing and new particle detectio...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Data |
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| Online Access: | https://www.mdpi.com/2306-5729/7/12/179 |
| _version_ | 1797460705635467264 |
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| author | Markus Vogelbacher Miao Zhang Krasimir Aleksandrov Hans-Joachim Gehrmann Jörg Matthes |
| author_facet | Markus Vogelbacher Miao Zhang Krasimir Aleksandrov Hans-Joachim Gehrmann Jörg Matthes |
| author_sort | Markus Vogelbacher |
| collection | DOAJ |
| description | This paper describes a benchmark dataset for the detection of fuel particles in 2D and 3D image data in a rotary kiln combustion chamber. The specific challenges of detecting the small particles under demanding environmental conditions allows for the performance of existing and new particle detection techniques to be evaluated. The data set includes a classification of burning and non-burning particles, which can be in the air but also on the rotary kiln wall. The light-field camera used for data generation offers the potential to develop and objectively evaluate new advanced particle detection methods due to the additional 3D information. Besides explanations of the data set and the contained ground truth, an evaluation procedure of the particle detection based on the ground truth and results for an own particle detection procedure for the data set are presented. |
| first_indexed | 2024-03-09T17:09:52Z |
| format | Article |
| id | doaj.art-ee805e5686b14ed587bfd5688803a536 |
| institution | Directory Open Access Journal |
| issn | 2306-5729 |
| language | English |
| last_indexed | 2024-03-09T17:09:52Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Data |
| spelling | doaj.art-ee805e5686b14ed587bfd5688803a5362023-11-24T14:13:57ZengMDPI AGData2306-57292022-12-0171217910.3390/data7120179Two- and Three-Dimensional Benchmarks for Particle Detection from an Industrial Rotary Kiln Combustion Chamber Based on Light-Field-Camera RecordingMarkus Vogelbacher0Miao Zhang1Krasimir Aleksandrov2Hans-Joachim Gehrmann3Jörg Matthes4Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, GermanyInstitute for Automation and Applied Informatics, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, GermanyInstitute for Technical Chemistry, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, GermanyInstitute for Technical Chemistry, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, GermanyInstitute for Automation and Applied Informatics, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, GermanyThis paper describes a benchmark dataset for the detection of fuel particles in 2D and 3D image data in a rotary kiln combustion chamber. The specific challenges of detecting the small particles under demanding environmental conditions allows for the performance of existing and new particle detection techniques to be evaluated. The data set includes a classification of burning and non-burning particles, which can be in the air but also on the rotary kiln wall. The light-field camera used for data generation offers the potential to develop and objectively evaluate new advanced particle detection methods due to the additional 3D information. Besides explanations of the data set and the contained ground truth, an evaluation procedure of the particle detection based on the ground truth and results for an own particle detection procedure for the data set are presented.https://www.mdpi.com/2306-5729/7/12/179benchmark3D point cloudparticle detectionlight-field camerarefuse-derived fuels |
| spellingShingle | Markus Vogelbacher Miao Zhang Krasimir Aleksandrov Hans-Joachim Gehrmann Jörg Matthes Two- and Three-Dimensional Benchmarks for Particle Detection from an Industrial Rotary Kiln Combustion Chamber Based on Light-Field-Camera Recording Data benchmark 3D point cloud particle detection light-field camera refuse-derived fuels |
| title | Two- and Three-Dimensional Benchmarks for Particle Detection from an Industrial Rotary Kiln Combustion Chamber Based on Light-Field-Camera Recording |
| title_full | Two- and Three-Dimensional Benchmarks for Particle Detection from an Industrial Rotary Kiln Combustion Chamber Based on Light-Field-Camera Recording |
| title_fullStr | Two- and Three-Dimensional Benchmarks for Particle Detection from an Industrial Rotary Kiln Combustion Chamber Based on Light-Field-Camera Recording |
| title_full_unstemmed | Two- and Three-Dimensional Benchmarks for Particle Detection from an Industrial Rotary Kiln Combustion Chamber Based on Light-Field-Camera Recording |
| title_short | Two- and Three-Dimensional Benchmarks for Particle Detection from an Industrial Rotary Kiln Combustion Chamber Based on Light-Field-Camera Recording |
| title_sort | two and three dimensional benchmarks for particle detection from an industrial rotary kiln combustion chamber based on light field camera recording |
| topic | benchmark 3D point cloud particle detection light-field camera refuse-derived fuels |
| url | https://www.mdpi.com/2306-5729/7/12/179 |
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